Datasets:
| dataset_info: | |
| features: | |
| - name: image | |
| dtype: image | |
| - name: label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': HLB | |
| '1': healthy | |
| splits: | |
| - name: train | |
| num_bytes: 1191138744 | |
| num_examples: 324 | |
| download_size: 1191169096 | |
| dataset_size: 1191138744 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| license: cc-by-4.0 | |
| task_categories: | |
| - image-classification | |
| size_categories: | |
| - n<1K | |
| # Orange Leaf Hlb Classification | |
| This dataset contains RGB images of orange leaves captured in a laboratory setting using multiple smartphone models. It is designed for computer vision research focused on detecting Huanglongbing disease and differentiating diseased leaves from non-diseased ones. The dataset contains 324 images across 2 classes: HLB, healthy. | |
| Images per class: | |
| - HLB: 195 | |
| - healthy: 129 | |
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. | |
| ## Citation | |
| ```bibtex | |
| <!-- TODO: add BibTeX citation --> | |
| ``` | |
| <!-- TODO: add plain text citation --> | |
| *This dataset was reformatted from its original format to match HuggingFace standards.* | |